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Machine Learning Research · 2023

Exoplanet Habitability Classification & Analysis

Comprehensive ML pipeline analyzing 5,600+ exoplanets from the PHL Exoplanet Catalog to predict habitability. Implemented multiple classification algorithms with model explainability using LIME to interpret planetary characteristics influencing habitability predictions.

Exoplanet habitability classification results and feature importance
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Technical highlights

  1. 01

    100+ feature engineering from astronomical measurements including ESI (Earth Similarity Index).

  2. 02

    Model explainability framework using LIME for interpretable habitability predictions.

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Stack

  • Python
  • Scikit-learn
  • Pandas
  • NumPy
  • Dask
  • LIME
  • Matplotlib